The proliferation of connected devices, together with the decreasing cost of storage, led to a huge growth on data being generated and collected every day, which can be leveraged by different organizations. However, storing and processing these huge amounts of data in a scalable and cost-effective way poses new challenges. This promoted the emergence of NoSQL database systems and processing solutions based on the MapReduce programming model as alternatives to the traditional Relational Database Management Systems (RDBMS) for large scale data processing. Those solutions, however, trade scalability for programmability, i.e. they sacrifice the standard SQL interface and ACID properties, and they are often specialized for certain workloads (transactional or analytical), requiring the use of different solutions for each workload. The CumuloNimbo platform is an alternative solution built on top of NoSQL systems, but that provides the benefits of traditional RDBMS (SQL language, ACID properties), thus maintaining compatibility with existing application stacks, and contributing to improve developers' productivity. CumuloNimbo achieves its scalability by decoupling and parallelizing components, and optimizing communications through asynchronous messaging and batching. Moreover, it was designed to scale with both transactional and analytical workloads, enabling the use of real-time data on analytics tasks, and eliminating the costs of ETLs and multiple systems